From a3372de0cba91c8c97ced1ae2c3a62692765829e Mon Sep 17 00:00:00 2001
From: dmarx <dmarx@users.noreply.github.com>
Date: Thu, 23 Nov 2023 16:57:18 +0000
Subject: [PATCH] deploy: fb95341f8c4324208829e04e4c0c6a026acce48d

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diff --git a/_sources/stubs/2019_RichSutton_TheBitterLesson.md b/_sources/stubs/2019_RichSutton_TheBitterLesson.md
new file mode 100644
index 00000000..e1f97aea
--- /dev/null
+++ b/_sources/stubs/2019_RichSutton_TheBitterLesson.md
@@ -0,0 +1,15 @@
+---
+jupytext:
+  formats: md:myst
+  text_representation:
+    extension: .md
+    format_name: myst
+kernelspec:
+  display_name: Python 3
+  language: python
+  name: python3
+---
+
+# "The Bitter Lesson"
+
+http://www.incompleteideas.net/IncIdeas/BitterLesson.html
\ No newline at end of file
diff --git a/content.html b/content.html
index 917fb276..885b9ec6 100644
--- a/content.html
+++ b/content.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="stubs/2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/genindex.html b/genindex.html
index cd901774..560dcd14 100644
--- a/genindex.html
+++ b/genindex.html
@@ -312,6 +312,7 @@
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="stubs/2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/intro.html b/intro.html
index 2665168e..29db433b 100644
--- a/intro.html
+++ b/intro.html
@@ -314,6 +314,7 @@
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="stubs/2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/markdown.html b/markdown.html
index 5d8204c0..f3314169 100644
--- a/markdown.html
+++ b/markdown.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="stubs/2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/notebooks.html b/notebooks.html
index 602190e4..4ba0e3b0 100644
--- a/notebooks.html
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 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="stubs/2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
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diff --git a/search.html b/search.html
index d5f76de3..00994d3d 100644
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 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="stubs/2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="stubs/2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
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"stubs/2022_BenPoole_DreamfusionTextTo3DUsing2DDiff.md", "stubs/2022_JasonWei_ChainOfThoughtPromptingElicits.md", "stubs/2022_JordanHoffmann_TrainingComputeOptimalLargeLan.md", "stubs/2022_LongOuyang_TrainingLanguageModelsToFollow.md", "stubs/2022_LucasBeyer_BetterPlainVitBaselinesForImag.md", "stubs/2022_RobinRombach_HighResolutionImageSynthesisWi.md", "stubs/2022_TeroKarras_ElucidatingTheDesignSpaceOfDif.md", "stubs/2022_WeixinLiang_MindTheGapUnderstandingTheModa.md", "stubs/2022_ZhuangLiu_AConvnetForThe2020S.md", "stubs/2022_ZimingLiu_TowardsUnderstandingGrokkingAn.md", "stubs/2023_AlexanderKirillov_SegmentAnything.md", "stubs/2023_AmirhosseinKazemnejad_TheImpactOfPositionalEncodingO.md", "stubs/2023_CharlieChen_AcceleratingLargeLanguageModel.md", "stubs/2023_MaximeOquab_Dinov2LearningRobustVisualFeat.md", "stubs/2023_MurrayShanahan_RolePlayWithLargeLanguageModel.md", "stubs/2023_TimoSchick_ToolformerLanguageModelsCanTea.md"], "titles": ["Content in Jupyter Book", "Welcome to your Jupyter Book", "Markdown Files", "Content with notebooks", "Read this PDF", "\u201cDistributional Structure\u201d", "\u201cA New Approach to Linear Filtering and Prediction Problems\u201d", "An Algorithm for the Machine Calculation of Complex Fourier Series", "\u201cNearest Neighbor Pattern Classification\u201d", "\u201cOn the uniform convergence of relative frequencies of events to their probabilities\u201d", "\u201cBootstrap Methods: Another Look at the Jackknife\u201d", "\u201cThe need for biases in learning generalizations\u201d", "\u201cSelf-Organized Formation of Topologically Correct Feature Maps\u201d", "CART) \u201cClassification and Regression Trees\u201d - in lieu of the book, here\u2019s a [topic summary from 2011", "\u201cA Theory of the Learnable\u201d", "\u201cExtensions_of_Lipschitz_mappings_into_a_Hilbert_space\u201d", "\u201cLearning representations by back-propagating errors\u201d", "ID3) [\u201cInduction of Decision Trees\u201d", "\u201cLearning to predict by the methods of temporal differences\u201d", "\u201cIndexing by Latent Semantic Analysis\u201d", "\u201cLearnability and the Vapnik-Chervonenkis Dimension \u201c", "\u201cLearning from Delayed Rewards\u201d", "\u201cMultilayer Feedforward Networks are Universal Approximators\u201d", "\u201cFast learning in multi-resolution hierarchies\u201d", "\u201cPrincipal Curves\u201d", "\u201cThe Strength of Weak Learnability\u201d", "\u201cRecurrent Networks and NARMA Modeling\u201d", "\u201cMultivariate Adaptive Regression Splines\u201d", "\u201cApproximation capabilities of multilayer feedforward networks\u201d", "\u201cBagging Predictors\u201d", "\u201cNonlinear principal component analysis using autoassociative neural networks\u201d", "\u201cFace Recognition Using Eigenfaces\u201d", "A Training Algorithm for Optimal Margin Classifier", "\u201cPrinciples of Risk Minimization for Learning Theory\u201d", "\u201cMultilayer Feedforward Networks With a Nonpolynomial Activation Function Can Approximate Any Function\u201d", "\u201cBayesian Methods for Neural Networks\u201d", "\u201cRegression Shrinkage and Selection via the Lasso\u201d", "\u201cNo Free Lunch Theorems for Optimization\u201d", "\u201cBidirectional Recurrent Neural Networks\u201d", "\u201cBias Plus Variance Decomposition for Zero-One Loss Functions\u201d", "\u201cLONG SHORT-TERM MEMORY\u201d", "AdaBoost) [\u201cA Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting\u201d", "\u201cThe PageRank Citation Ranking: Bringing Order to the Web\u201d", "\u201cEfficient Backprop\u201d", "\u201cGradientBased Learning Applied to Document Recognition\u201d", "\u201cGeneralization in a linear perceptron in the presence of noise\u201d", "\u201cImproved Boosting Algorithms Using Confidence-rated Predictions\u201d", "\u201cRandom Forests\u201d", "\u201cOn Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes", "\u201cStochastic Neighbor Embedding\u201d", "\u201cSmote: synthetic minority over-sampling technique\u201d", "\u201cLearning From Labeled and Unlabeled Data With Label Propagation\u201d", "\u201cLatent Dirichlet Allocation\u201d", "\u201cGradient Flow in Recurrent Nets: the Difficulty of Learning Long-Term Dependencies\u201d", "\u201cDocument Clustering Based On Non-negative Matrix Factorization\u201d", "\u201cFinding community structure in very large networks\u201d", "\u201cModel Compression\u201d", "\u201cRegularization and variable selection via the elastic net\u201d", "\u201cHow To Break Anonymity of the Netflix Prize Dataset\u201d", "\u201cReducing the Dimensionality of Data with Neural Networks\u201d", "\u201cThe Netflix Prize\u201d", "\u201cThe BellKor solution to the Netflix Prize\u201d", "\u201cThe BigChaos Solution to the Netflix Prize 2008\u201d", "\u201cVisualizing Data using t-SNE\u201d", "Group theoretical methods in machine learning (thesis)", "\u201cThe BellKor 2008 Solution to the Netflix Prize\u201d", "\u201cFast unfolding of communities in large networks\u201d", "\u201cFeature Hashing for Large Scale Multitask Learning\u201d", "\u201cGaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design\u201d", "\u201cFeature Selection with the Boruta Package\u201d", "\u201cRecurrent neural network based language model\u201d", "\u201cUnderstanding the difficulty of training deep feedforward neural networks\u201d", "\u201cHOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent\u201d", "\u201cDeep Sparse Rectifier Neural Networks\u201d", "using ImageNet leaderboard date; article published 2017) - [\u201cImageNet Classification with Deep Convolutional Neural Networks\u201d", "\u201cRandom Search for Hyper-Parameter Optimization\u201d", "ESTIMATING UNCERTAINTY FOR MASSIVE DATA STREAMS", "\u201cAuto-Encoding Variational Bayes\u201d", "\u201cUnderstanding Dropout\u201d", "\u201cDistributed Representations of Words and Phrases and their Compositionality\u201d", "DQN) [\u201cPlaying Atari with Deep Reinforcement Learning\u201d", "\u201cGenerating Sequences With Recurrent Neural Networks\u201d", "\u201cDeep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images\u201d", "\u201cUnderstanding Deep Image Representations by Inverting Them\u201d", "\u201cAdam: A Method for Stochastic Optimization\u201d", "\u201cNeural Machine Translation by Jointly Learning to Align and Translate\u201d", "\u201cSequence to Sequence Learning with Neural Networks\u201d", "\u201cVery Deep Convolutional Networks for Large-Scale Image Recognition\u201d", "\u201cDropout: A Simple Way to Prevent Neural Networks from Overfitting\u201d", "\u201cNeural Word Embedding as Implicit Matrix Factorization\u201d", "\u201cIdentifying and attacking the saddle point problem in high-dimensional non-convex optimization\u201d", "\u201cLOCALITY PRESERVING HASHING\u201d", "\u201cOn the Properties of Neural Machine Translation: Encoder\u2013Decoder Approaches\u201d", "\u201cInceptionism: Going Deeper into Neural Networks\u201d", "\u201cHidden Technical Debt in Machine Learning Systems\u201d", "\u201cDistilling the Knowledge in a Neural Network\u201d", "\u201cSiamese Neural Networks for One-Shot Image Recognition\u201d", "\u201cDeep Unsupervised Learning using Nonequilibrium Thermodynamics\u201d", "\u201cDeep Residual Learning for Image Recognition\u201d", "\u201cDeep Learning and the Information Bottleneck Principle\u201d", "\u201cNeural Machine Translation of Rare Words with Subword Units\u201d", "\u201cHighway Networks\u201d", "\u201cBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift\u201d", "\u201cHuman-level control through deep reinforcement learning\u201d", "\u201cDropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning\u201d", "\u201cWaveNet: A Generative Model for Raw Audio\u201d", "\u201cUnderstanding deep learning requires rethinking generalization\u201d", "\u201cGaussian Error Linear Units (GELUs)\u201d", "\u201cCategorical Reparameterization with Gumbel-Softmax\u201d", "\u201cArtistic style transfer for videos\u201d", "\u201cXGBoost: A Scalable Tree Boosting System\u201d", "\u201cFeature Pyramid Networks for Object Detection\u201d", "\u201cDouble/Debiased Machine Learning for Treatment and Causal Parameters\u201d", "\u201cGoogle\u2019s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation\u201d", "\u201cHyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization\u201d", "\u201cNeural Discrete Representation Learning\u201d", "\u201cA Multi-Horizon Quantile Recurrent Forecaster\u201d", "\u201cSMASH: One-Shot Model Architecture Search through HyperNetworks\u201d", "\u201cMobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications\u201d", "\u201cAttention Is All You Need\u201d", "\u201cOn the Properties of the Softmax Function with Application in Game Theory and Reinforcement Learning\u201d", "\u201cOn Calibration of Modern Neural Networks\u201d", "\u201cSqueeze-and-Excitation Networks\u201d", "\u201cProximal Policy Optimization Algorithms\u201d", "\u201cMask R-CNN\u201d", "\u201cAnalysis of dropout learning regarded as ensemble learning\u201d", "\u201cGANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium\u201d", "\u201cStochastic Gradient Descent as Approximate Bayesian Inference\u201d", "\u201cArbitrary Style Transfer in Real-time with Adaptive Instance Normalization\u201d", "\u201cA Structured Self-attentive Sentence Embedding\u201d", "\u201cRepresentation Learning with Contrastive Predictive Coding\u201d", "\u201cNeural Tangent Kernel: Convergence and Generalization in Neural Networks\u201d", "\u201cTracking Emerges by Colorizing Videos\u201d", "\u201cDeep Image Prior\u201d", "\u201cBERT: Pre-training of Deep Bidirectional Transformers for Language Understanding\u201d", "\u201cThe 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"stubs/2023_TimoSchick_ToolformerLanguageModelsCanTea.md"], "titles": ["Content in Jupyter Book", "Welcome to your Jupyter Book", "Markdown Files", "Content with notebooks", "Read this PDF", "\u201cDistributional Structure\u201d", "\u201cA New Approach to Linear Filtering and Prediction Problems\u201d", "An Algorithm for the Machine Calculation of Complex Fourier Series", "\u201cNearest Neighbor Pattern Classification\u201d", "\u201cOn the uniform convergence of relative frequencies of events to their probabilities\u201d", "\u201cBootstrap Methods: Another Look at the Jackknife\u201d", "\u201cThe need for biases in learning generalizations\u201d", "\u201cSelf-Organized Formation of Topologically Correct Feature Maps\u201d", "CART) \u201cClassification and Regression Trees\u201d - in lieu of the book, here\u2019s a [topic summary from 2011", "\u201cA Theory of the Learnable\u201d", "\u201cExtensions_of_Lipschitz_mappings_into_a_Hilbert_space\u201d", "\u201cLearning representations by back-propagating errors\u201d", "ID3) [\u201cInduction of Decision Trees\u201d", "\u201cLearning to predict by the methods of temporal differences\u201d", "\u201cIndexing by Latent Semantic Analysis\u201d", "\u201cLearnability and the Vapnik-Chervonenkis Dimension \u201c", "\u201cLearning from Delayed Rewards\u201d", "\u201cMultilayer Feedforward Networks are Universal Approximators\u201d", "\u201cFast learning in multi-resolution hierarchies\u201d", "\u201cPrincipal Curves\u201d", "\u201cThe Strength of Weak Learnability\u201d", "\u201cRecurrent Networks and NARMA Modeling\u201d", "\u201cMultivariate Adaptive Regression Splines\u201d", "\u201cApproximation capabilities of multilayer feedforward networks\u201d", "\u201cBagging Predictors\u201d", "\u201cNonlinear principal component analysis using autoassociative neural networks\u201d", "\u201cFace Recognition Using Eigenfaces\u201d", "A Training Algorithm for Optimal Margin Classifier", "\u201cPrinciples of Risk Minimization for Learning Theory\u201d", "\u201cMultilayer Feedforward Networks With a Nonpolynomial Activation Function Can Approximate Any Function\u201d", "\u201cBayesian Methods for Neural Networks\u201d", "\u201cRegression Shrinkage and Selection via the Lasso\u201d", "\u201cNo Free Lunch Theorems for Optimization\u201d", "\u201cBidirectional Recurrent Neural Networks\u201d", "\u201cBias Plus Variance Decomposition for Zero-One Loss Functions\u201d", "\u201cLONG SHORT-TERM MEMORY\u201d", "AdaBoost) [\u201cA Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting\u201d", "\u201cThe PageRank Citation Ranking: Bringing Order to the Web\u201d", "\u201cEfficient Backprop\u201d", "\u201cGradientBased Learning Applied to Document Recognition\u201d", "\u201cGeneralization in a linear perceptron in the presence of noise\u201d", "\u201cImproved Boosting Algorithms Using Confidence-rated Predictions\u201d", "\u201cRandom Forests\u201d", "\u201cOn Discriminative vs. Generative classifiers: A comparison of logistic regression and naive Bayes", "\u201cStochastic Neighbor Embedding\u201d", "\u201cSmote: synthetic minority over-sampling technique\u201d", "\u201cLearning From Labeled and Unlabeled Data With Label Propagation\u201d", "\u201cLatent Dirichlet Allocation\u201d", "\u201cGradient Flow in Recurrent Nets: the Difficulty of Learning Long-Term Dependencies\u201d", "\u201cDocument Clustering Based On Non-negative Matrix Factorization\u201d", "\u201cFinding community structure in very large networks\u201d", "\u201cModel Compression\u201d", "\u201cRegularization and variable selection via the elastic net\u201d", "\u201cHow To Break Anonymity of the Netflix Prize Dataset\u201d", "\u201cReducing the Dimensionality of Data with Neural Networks\u201d", "\u201cThe Netflix Prize\u201d", "\u201cThe BellKor solution to the Netflix Prize\u201d", "\u201cThe BigChaos Solution to the Netflix Prize 2008\u201d", "\u201cVisualizing Data using t-SNE\u201d", "Group 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"\u201cUnderstanding Dropout\u201d", "\u201cDistributed Representations of Words and Phrases and their Compositionality\u201d", "DQN) [\u201cPlaying Atari with Deep Reinforcement Learning\u201d", "\u201cGenerating Sequences With Recurrent Neural Networks\u201d", "\u201cDeep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images\u201d", "\u201cUnderstanding Deep Image Representations by Inverting Them\u201d", "\u201cAdam: A Method for Stochastic Optimization\u201d", "\u201cNeural Machine Translation by Jointly Learning to Align and Translate\u201d", "\u201cSequence to Sequence Learning with Neural Networks\u201d", "\u201cVery Deep Convolutional Networks for Large-Scale Image Recognition\u201d", "\u201cDropout: A Simple Way to Prevent Neural Networks from Overfitting\u201d", "\u201cNeural Word Embedding as Implicit Matrix Factorization\u201d", "\u201cIdentifying and attacking the saddle point problem in high-dimensional non-convex optimization\u201d", "\u201cLOCALITY PRESERVING HASHING\u201d", "\u201cOn the Properties of Neural Machine Translation: Encoder\u2013Decoder Approaches\u201d", "\u201cInceptionism: Going Deeper into Neural Networks\u201d", "\u201cHidden Technical Debt in Machine Learning Systems\u201d", "\u201cDistilling the Knowledge in a Neural Network\u201d", "\u201cSiamese Neural Networks for One-Shot Image Recognition\u201d", "\u201cDeep Unsupervised Learning using Nonequilibrium Thermodynamics\u201d", "\u201cDeep Residual Learning for Image Recognition\u201d", "\u201cDeep Learning and the Information Bottleneck Principle\u201d", "\u201cNeural Machine Translation of Rare Words with Subword Units\u201d", "\u201cHighway Networks\u201d", "\u201cBatch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift\u201d", "\u201cHuman-level control through deep reinforcement learning\u201d", "\u201cDropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning\u201d", "\u201cWaveNet: A Generative Model for Raw Audio\u201d", "\u201cUnderstanding deep learning requires rethinking generalization\u201d", "\u201cGaussian Error Linear Units (GELUs)\u201d", "\u201cCategorical Reparameterization with Gumbel-Softmax\u201d", "\u201cArtistic style transfer for videos\u201d", "\u201cXGBoost: A Scalable Tree Boosting System\u201d", "\u201cFeature Pyramid Networks for Object Detection\u201d", "\u201cDouble/Debiased Machine Learning for Treatment and Causal Parameters\u201d", "\u201cGoogle\u2019s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation\u201d", "\u201cHyperband: A Novel Bandit-Based Approach to Hyperparameter Optimization\u201d", "\u201cNeural Discrete Representation Learning\u201d", "\u201cA Multi-Horizon Quantile Recurrent Forecaster\u201d", "\u201cSMASH: One-Shot Model Architecture Search through HyperNetworks\u201d", "\u201cMobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications\u201d", "\u201cAttention Is All You Need\u201d", "\u201cOn the Properties of the Softmax Function with Application in Game Theory and Reinforcement Learning\u201d", "\u201cOn Calibration of Modern Neural Networks\u201d", "\u201cSqueeze-and-Excitation Networks\u201d", "\u201cProximal Policy Optimization Algorithms\u201d", "\u201cMask R-CNN\u201d", "\u201cAnalysis of dropout learning regarded as ensemble learning\u201d", "\u201cGANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium\u201d", "\u201cStochastic Gradient Descent as Approximate Bayesian Inference\u201d", "\u201cArbitrary Style Transfer in Real-time with Adaptive Instance Normalization\u201d", "\u201cA Structured Self-attentive Sentence Embedding\u201d", "\u201cRepresentation Learning with Contrastive Predictive Coding\u201d", "\u201cNeural Tangent Kernel: Convergence and Generalization in Neural Networks\u201d", "\u201cTracking Emerges by Colorizing Videos\u201d", "\u201cDeep Image Prior\u201d", "\u201cBERT: Pre-training of Deep Bidirectional Transformers for Language Understanding\u201d", "\u201cThe Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks\u201d", "\u201cOccupancy Networks: Learning 3D Reconstruction in Function Space\u201d", "\u201cUMAP: Uniform Manifold Approximation and Projection for Dimension Reduction\u201d", "\u201cMobileNetV2: Inverted Residuals and Linear Bottlenecks\u201d", "\u201cRelational inductive biases, deep learning, and graph networks\u201d", "A Spline Theory of Deep Networks", "\u201cUnderstanding the Disharmony between Dropout and Batch Normalization by Variance Shift\u201d", "\u201cGenerating Diverse High-Fidelity Images with VQ-VAE-2\u201d", "\u201cOn the Measure of Intelligence\u201d", "\u201cReconciling modern machine-learning practice and the classical bias\u2013variance trade-off\u201d", "\u201cEfficientNet: Rethinking Model Scaling for Convolutional Neural Networks\u201d", "\u201cOn the covariance-Hessian relation in evolution strategies\u201d", "\u201cDeep Double Descent: Where Bigger Models and More Data Hurt\u201d", "\u201cThe Bitter Lesson\u201d", "\u201cZeRO: Memory Optimizations Toward Training Trillion Parameter Models\u201d", "\u201cAn Image is Worth 16x16 Words: Transformers for Image Recognition at Scale\u201d", "\u201cBayesian workflow\u201d", "\u201cIntrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning\u201d", "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis", "\u201cDenoising Diffusion Probabilistic Models\u201d", "\u201cTaming Transformers for High-Resolution Image Synthesis\u201d", "\u201cThe generalization error of random features regression: Precise asymptotics and double descent curve", "\u201cLanguage Models are Few-Shot Learners\u201d", "Implicit Neural Representations with Periodic Activation Functions", "Learning Transferable Visual Models From Natural Language Supervision", "Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets", "\u201cAn Introduction to Johnson-Lindenstrauss Transforms\u201d", "\u201cSDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations\u201d", "\u201cLoRA: Low-Rank Adaptation of Large Language Models\u201d", "\u201cHighly accurate protein structure prediction with AlphaFold\u201d", "Classifier-Free Diffusion Guidance", "\u201cEmerging Properties in Self-Supervised Vision Transformers\u201d", "Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges", "\u201cLearning in High Dimension Always Amounts to Extrapolation\u201d", "\u201cA Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning\u201d", "\u201cCold Diffusion: Inverting Arbitrary Image Transforms Without Noise\u201d", "\u201cDreamFusion: Text-to-3D using 2D Diffusion\u201d", "\u201cChain-of-Thought Prompting Elicits Reasoning in Large Language Models\u201d", "\u201cTraining Compute-Optimal Large Language Models\u201d", "\u201cTraining language models to follow instructions with human feedback\u201d", "\u201cBetter plain ViT baselines for ImageNet-1k\u201d", "\u201cHigh-Resolution Image Synthesis with Latent Diffusion Models\u201d", "\u201cElucidating the Design Space of Diffusion-Based Generative Models\u201d", "\u201cMind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning\u201d", "\u201cA ConvNet for the 2020s\u201d", "Towards Understanding Grokking: An Effective Theory of Representation Learning", "\u201cSegment Anything\u201d", "\u201cThe Impact of Positional Encoding on Length Generalization in Transformers\u201d", "\u201cAccelerating Large Language Model Decoding with Speculative Sampling\u201d", "\u201cDINOv2: Learning Robust Visual Features without Supervision\u201d", "\u201cRole-Play with Large Language Models\u201d", "\u201cToolformer: Language Models Can Teach Themselves to Use Tools\u201d"], "terms": {"There": [0, 2, 3], "ar": 0, "mani": [0, 2], "wai": [0, 4], "write": [0, 2], "thi": [0, 1, 2, 3], "short": 0, "section": 0, "cover": 0, "few": 0, "tip": 0, "how": [0, 1], "do": [0, 2, 3], "so": [0, 2], "small": [1, 2], "sampl": [1, 3], "give": 1, "you": [1, 2, 3, 4], "feel": 1, "content": [1, 2, 17, 18, 35, 47], "structur": [1, 2], "here": [1, 2, 3], "note": [1, 2], "And": 1, "code": 1, "block": [1, 2], "e": 1, "mc": 1, "2": [1, 57, 164], "check": [1, 3], "out": [1, 3], "page": [1, 2, 13], "bundl": 1, "see": [1, 2, 3], "more": [1, 2, 3], "whether": 2, "book": [2, 3], "s": [2, 3], "jupyt": [2, 3], "notebook": 2, "ipynb": 2, "regular": 2, "md": 2, "ll": 2, "same": 2, 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diff --git a/stubs/1954_ZelligHarris_DistributionalStructure.html b/stubs/1954_ZelligHarris_DistributionalStructure.html
index 4ccc7bef..1bac778c 100644
--- a/stubs/1954_ZelligHarris_DistributionalStructure.html
+++ b/stubs/1954_ZelligHarris_DistributionalStructure.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1960_REKalman_ANewApproachToLinearFilteringA.html b/stubs/1960_REKalman_ANewApproachToLinearFilteringA.html
index 0d0cd685..6f26696b 100644
--- a/stubs/1960_REKalman_ANewApproachToLinearFilteringA.html
+++ b/stubs/1960_REKalman_ANewApproachToLinearFilteringA.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1965_JamesCooley_AnAlgorithmForTheMachineCalcul.html b/stubs/1965_JamesCooley_AnAlgorithmForTheMachineCalcul.html
index 9f2fc4d7..870fc80b 100644
--- a/stubs/1965_JamesCooley_AnAlgorithmForTheMachineCalcul.html
+++ b/stubs/1965_JamesCooley_AnAlgorithmForTheMachineCalcul.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1967_TMCover_NearestNeighborPatternClassifi.html b/stubs/1967_TMCover_NearestNeighborPatternClassifi.html
index c15fd92c..a136cfbe 100644
--- a/stubs/1967_TMCover_NearestNeighborPatternClassifi.html
+++ b/stubs/1967_TMCover_NearestNeighborPatternClassifi.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1971_VVapnikAndAChervonenkis_OnTheUniformConvergenceOfRelat.html b/stubs/1971_VVapnikAndAChervonenkis_OnTheUniformConvergenceOfRelat.html
index 2259d281..37ae2ac0 100644
--- a/stubs/1971_VVapnikAndAChervonenkis_OnTheUniformConvergenceOfRelat.html
+++ b/stubs/1971_VVapnikAndAChervonenkis_OnTheUniformConvergenceOfRelat.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1979_BradleyEffron_BootstrapMethodsAnotherLookAtT.html b/stubs/1979_BradleyEffron_BootstrapMethodsAnotherLookAtT.html
index 17e7893a..94404b8a 100644
--- a/stubs/1979_BradleyEffron_BootstrapMethodsAnotherLookAtT.html
+++ b/stubs/1979_BradleyEffron_BootstrapMethodsAnotherLookAtT.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1980_TomMitchell_TheNeedForBiasesInLearningGene.html b/stubs/1980_TomMitchell_TheNeedForBiasesInLearningGene.html
index 20102b00..4db11499 100644
--- a/stubs/1980_TomMitchell_TheNeedForBiasesInLearningGene.html
+++ b/stubs/1980_TomMitchell_TheNeedForBiasesInLearningGene.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1982_TeuvoKohonen_SelfOrganizedFormationOfTopolo.html b/stubs/1982_TeuvoKohonen_SelfOrganizedFormationOfTopolo.html
index bc9dbf69..42b19d42 100644
--- a/stubs/1982_TeuvoKohonen_SelfOrganizedFormationOfTopolo.html
+++ b/stubs/1982_TeuvoKohonen_SelfOrganizedFormationOfTopolo.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1984_BreimanL_CartClassificationAndRegressio.html b/stubs/1984_BreimanL_CartClassificationAndRegressio.html
index b273e9fe..1281332c 100644
--- a/stubs/1984_BreimanL_CartClassificationAndRegressio.html
+++ b/stubs/1984_BreimanL_CartClassificationAndRegressio.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1984_LGValiant_ATheoryOfTheLearnable.html b/stubs/1984_LGValiant_ATheoryOfTheLearnable.html
index 8edab778..df979171 100644
--- a/stubs/1984_LGValiant_ATheoryOfTheLearnable.html
+++ b/stubs/1984_LGValiant_ATheoryOfTheLearnable.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1984_WilliamBJohnson_ExtensionsOfLipschitzMappingsI.html b/stubs/1984_WilliamBJohnson_ExtensionsOfLipschitzMappingsI.html
index a69d6840..88efb03d 100644
--- a/stubs/1984_WilliamBJohnson_ExtensionsOfLipschitzMappingsI.html
+++ b/stubs/1984_WilliamBJohnson_ExtensionsOfLipschitzMappingsI.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
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diff --git a/stubs/1986_DavidRumelhart_LearningRepresentationsByBackP.html b/stubs/1986_DavidRumelhart_LearningRepresentationsByBackP.html
index 1468f2a0..8cc5fa44 100644
--- a/stubs/1986_DavidRumelhart_LearningRepresentationsByBackP.html
+++ b/stubs/1986_DavidRumelhart_LearningRepresentationsByBackP.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1986_JRQuinlan_Id3InductionOfDecisionTrees.html b/stubs/1986_JRQuinlan_Id3InductionOfDecisionTrees.html
index 9e98c5db..e8667c3e 100644
--- a/stubs/1986_JRQuinlan_Id3InductionOfDecisionTrees.html
+++ b/stubs/1986_JRQuinlan_Id3InductionOfDecisionTrees.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1988_RichardSSutton_LearningToPredictByTheMethodsO.html b/stubs/1988_RichardSSutton_LearningToPredictByTheMethodsO.html
index 878e542a..1f601316 100644
--- a/stubs/1988_RichardSSutton_LearningToPredictByTheMethodsO.html
+++ b/stubs/1988_RichardSSutton_LearningToPredictByTheMethodsO.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1988_ScottDeerwester_IndexingByLatentSemanticAnalys.html b/stubs/1988_ScottDeerwester_IndexingByLatentSemanticAnalys.html
index 57ea92f0..2b5e41e8 100644
--- a/stubs/1988_ScottDeerwester_IndexingByLatentSemanticAnalys.html
+++ b/stubs/1988_ScottDeerwester_IndexingByLatentSemanticAnalys.html
@@ -315,6 +315,7 @@
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+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
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diff --git a/stubs/1989_Blumer_LearnabilityAndTheVapnikChervo.html b/stubs/1989_Blumer_LearnabilityAndTheVapnikChervo.html
index b210d8f9..ed700570 100644
--- a/stubs/1989_Blumer_LearnabilityAndTheVapnikChervo.html
+++ b/stubs/1989_Blumer_LearnabilityAndTheVapnikChervo.html
@@ -315,6 +315,7 @@
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+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
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diff --git a/stubs/1989_ChristopherWatkins_LearningFromDelayedRewards.html b/stubs/1989_ChristopherWatkins_LearningFromDelayedRewards.html
index 4193cdce..4edffa85 100644
--- a/stubs/1989_ChristopherWatkins_LearningFromDelayedRewards.html
+++ b/stubs/1989_ChristopherWatkins_LearningFromDelayedRewards.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1989_Hornik_MultilayerFeedforwardNetworksA.html b/stubs/1989_Hornik_MultilayerFeedforwardNetworksA.html
index ce3f4c90..ca62e326 100644
--- a/stubs/1989_Hornik_MultilayerFeedforwardNetworksA.html
+++ b/stubs/1989_Hornik_MultilayerFeedforwardNetworksA.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1989_JohnMoody_FastLearningInMultiResolutionH.html b/stubs/1989_JohnMoody_FastLearningInMultiResolutionH.html
index 3f49d02c..921e1b3a 100644
--- a/stubs/1989_JohnMoody_FastLearningInMultiResolutionH.html
+++ b/stubs/1989_JohnMoody_FastLearningInMultiResolutionH.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1989_TrevorHastie_PrincipalCurves.html b/stubs/1989_TrevorHastie_PrincipalCurves.html
index fa70f369..bd81bb7b 100644
--- a/stubs/1989_TrevorHastie_PrincipalCurves.html
+++ b/stubs/1989_TrevorHastie_PrincipalCurves.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1990_RobertESchapire_TheStrengthOfWeakLearnability.html b/stubs/1990_RobertESchapire_TheStrengthOfWeakLearnability.html
index d4d70852..0e801cc1 100644
--- a/stubs/1990_RobertESchapire_TheStrengthOfWeakLearnability.html
+++ b/stubs/1990_RobertESchapire_TheStrengthOfWeakLearnability.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1991_JConnor_RecurrentNetworksAndNarmaModel.html b/stubs/1991_JConnor_RecurrentNetworksAndNarmaModel.html
index 5850e2e3..7dea389b 100644
--- a/stubs/1991_JConnor_RecurrentNetworksAndNarmaModel.html
+++ b/stubs/1991_JConnor_RecurrentNetworksAndNarmaModel.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1991_JeromeHFriedman_MultivariateAdaptiveRegression.html b/stubs/1991_JeromeHFriedman_MultivariateAdaptiveRegression.html
index e3ad8a9f..4cc3e542 100644
--- a/stubs/1991_JeromeHFriedman_MultivariateAdaptiveRegression.html
+++ b/stubs/1991_JeromeHFriedman_MultivariateAdaptiveRegression.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1991_KurtHornik_ApproximationCapabilitiesOfMul.html b/stubs/1991_KurtHornik_ApproximationCapabilitiesOfMul.html
index 3caa97e8..1321ca4b 100644
--- a/stubs/1991_KurtHornik_ApproximationCapabilitiesOfMul.html
+++ b/stubs/1991_KurtHornik_ApproximationCapabilitiesOfMul.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1991_LeoBreiman_BaggingPredictors.html b/stubs/1991_LeoBreiman_BaggingPredictors.html
index 92d4ab26..9d1ec5a2 100644
--- a/stubs/1991_LeoBreiman_BaggingPredictors.html
+++ b/stubs/1991_LeoBreiman_BaggingPredictors.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1991_MarkAKramer_NonlinearPrincipalComponentAna.html b/stubs/1991_MarkAKramer_NonlinearPrincipalComponentAna.html
index 54ca8817..c605f915 100644
--- a/stubs/1991_MarkAKramer_NonlinearPrincipalComponentAna.html
+++ b/stubs/1991_MarkAKramer_NonlinearPrincipalComponentAna.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1991_MatthewTurk_FaceRecognitionUsingEigenfaces.html b/stubs/1991_MatthewTurk_FaceRecognitionUsingEigenfaces.html
index fee61c02..fa4cc2de 100644
--- a/stubs/1991_MatthewTurk_FaceRecognitionUsingEigenfaces.html
+++ b/stubs/1991_MatthewTurk_FaceRecognitionUsingEigenfaces.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1992_BernhardEBoser_ATrainingAlgorithmForOptimalMa.html b/stubs/1992_BernhardEBoser_ATrainingAlgorithmForOptimalMa.html
index b19e03a2..c8722490 100644
--- a/stubs/1992_BernhardEBoser_ATrainingAlgorithmForOptimalMa.html
+++ b/stubs/1992_BernhardEBoser_ATrainingAlgorithmForOptimalMa.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1992_VVapnik_PrinciplesOfRiskMinimizationFo.html b/stubs/1992_VVapnik_PrinciplesOfRiskMinimizationFo.html
index a293acbf..dcd41a4c 100644
--- a/stubs/1992_VVapnik_PrinciplesOfRiskMinimizationFo.html
+++ b/stubs/1992_VVapnik_PrinciplesOfRiskMinimizationFo.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1993_MosheLeshno_MultilayerFeedforwardNetworksW.html b/stubs/1993_MosheLeshno_MultilayerFeedforwardNetworksW.html
index 8b01b6bb..fb5933f1 100644
--- a/stubs/1993_MosheLeshno_MultilayerFeedforwardNetworksW.html
+++ b/stubs/1993_MosheLeshno_MultilayerFeedforwardNetworksW.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1995_ChristopherBishop_BayesianMethodsForNeuralNetwor.html b/stubs/1995_ChristopherBishop_BayesianMethodsForNeuralNetwor.html
index 4a7b6f12..3620a8fd 100644
--- a/stubs/1995_ChristopherBishop_BayesianMethodsForNeuralNetwor.html
+++ b/stubs/1995_ChristopherBishop_BayesianMethodsForNeuralNetwor.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1996_RobertTibshirani_RegressionShrinkageAndSelectio.html b/stubs/1996_RobertTibshirani_RegressionShrinkageAndSelectio.html
index bb6334a7..981b0d91 100644
--- a/stubs/1996_RobertTibshirani_RegressionShrinkageAndSelectio.html
+++ b/stubs/1996_RobertTibshirani_RegressionShrinkageAndSelectio.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1997_DavidHWolpert_NoFreeLunchTheoremsForOptimiza.html b/stubs/1997_DavidHWolpert_NoFreeLunchTheoremsForOptimiza.html
index 67b47820..9fc478a4 100644
--- a/stubs/1997_DavidHWolpert_NoFreeLunchTheoremsForOptimiza.html
+++ b/stubs/1997_DavidHWolpert_NoFreeLunchTheoremsForOptimiza.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1997_MikeSchuster_BidirectionalRecurrentNeuralNe.html b/stubs/1997_MikeSchuster_BidirectionalRecurrentNeuralNe.html
index 53faba40..5b6240b0 100644
--- a/stubs/1997_MikeSchuster_BidirectionalRecurrentNeuralNe.html
+++ b/stubs/1997_MikeSchuster_BidirectionalRecurrentNeuralNe.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1997_RonKohavi_BiasPlusVarianceDecompositionF.html b/stubs/1997_RonKohavi_BiasPlusVarianceDecompositionF.html
index b97ce188..98b973dc 100644
--- a/stubs/1997_RonKohavi_BiasPlusVarianceDecompositionF.html
+++ b/stubs/1997_RonKohavi_BiasPlusVarianceDecompositionF.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1997_SeppHochreiter_LongShortTermMemory.html b/stubs/1997_SeppHochreiter_LongShortTermMemory.html
index 5278c3a3..12bcc34d 100644
--- a/stubs/1997_SeppHochreiter_LongShortTermMemory.html
+++ b/stubs/1997_SeppHochreiter_LongShortTermMemory.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1997_YoavFreund_AdaboostADecisionTheoreticGene.html b/stubs/1997_YoavFreund_AdaboostADecisionTheoreticGene.html
index f4a1c1e2..c36c4be7 100644
--- a/stubs/1997_YoavFreund_AdaboostADecisionTheoreticGene.html
+++ b/stubs/1997_YoavFreund_AdaboostADecisionTheoreticGene.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1998_LarryPage_ThePagerankCitationRankingBrin.html b/stubs/1998_LarryPage_ThePagerankCitationRankingBrin.html
index 4f3a4a12..225f1635 100644
--- a/stubs/1998_LarryPage_ThePagerankCitationRankingBrin.html
+++ b/stubs/1998_LarryPage_ThePagerankCitationRankingBrin.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1998_YannLecun_EfficientBackprop.html b/stubs/1998_YannLecun_EfficientBackprop.html
index 675729d0..c1a0caed 100644
--- a/stubs/1998_YannLecun_EfficientBackprop.html
+++ b/stubs/1998_YannLecun_EfficientBackprop.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1998_YannLecun_GradientbasedLearningAppliedTo.html b/stubs/1998_YannLecun_GradientbasedLearningAppliedTo.html
index 94cf3ff4..75cee808 100644
--- a/stubs/1998_YannLecun_GradientbasedLearningAppliedTo.html
+++ b/stubs/1998_YannLecun_GradientbasedLearningAppliedTo.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1999_AndersKrogh_GeneralizationInALinearPercept.html b/stubs/1999_AndersKrogh_GeneralizationInALinearPercept.html
index a9d55323..dd3a272d 100644
--- a/stubs/1999_AndersKrogh_GeneralizationInALinearPercept.html
+++ b/stubs/1999_AndersKrogh_GeneralizationInALinearPercept.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/1999_YoavFreund_ImprovedBoostingAlgorithmsUsin.html b/stubs/1999_YoavFreund_ImprovedBoostingAlgorithmsUsin.html
index 0fad3df6..baa9c7ca 100644
--- a/stubs/1999_YoavFreund_ImprovedBoostingAlgorithmsUsin.html
+++ b/stubs/1999_YoavFreund_ImprovedBoostingAlgorithmsUsin.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2001_LeoBreiman_RandomForests.html b/stubs/2001_LeoBreiman_RandomForests.html
index 70c9aa76..f102738c 100644
--- a/stubs/2001_LeoBreiman_RandomForests.html
+++ b/stubs/2001_LeoBreiman_RandomForests.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2002_AndrewNg_OnDiscriminativeVsGenerativeCl.html b/stubs/2002_AndrewNg_OnDiscriminativeVsGenerativeCl.html
index ebd47225..05ee6492 100644
--- a/stubs/2002_AndrewNg_OnDiscriminativeVsGenerativeCl.html
+++ b/stubs/2002_AndrewNg_OnDiscriminativeVsGenerativeCl.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2002_GeoffreyHinton_StochasticNeighborEmbedding.html b/stubs/2002_GeoffreyHinton_StochasticNeighborEmbedding.html
index e8391305..f6c18629 100644
--- a/stubs/2002_GeoffreyHinton_StochasticNeighborEmbedding.html
+++ b/stubs/2002_GeoffreyHinton_StochasticNeighborEmbedding.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2002_NiteshVChawla_SmoteSyntheticMinorityOverSamp.html b/stubs/2002_NiteshVChawla_SmoteSyntheticMinorityOverSamp.html
index bedac042..10bb736e 100644
--- a/stubs/2002_NiteshVChawla_SmoteSyntheticMinorityOverSamp.html
+++ b/stubs/2002_NiteshVChawla_SmoteSyntheticMinorityOverSamp.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2002_XiaojinZhu_LearningFromLabeledAndUnlabele.html b/stubs/2002_XiaojinZhu_LearningFromLabeledAndUnlabele.html
index e6f74247..7a1c2009 100644
--- a/stubs/2002_XiaojinZhu_LearningFromLabeledAndUnlabele.html
+++ b/stubs/2002_XiaojinZhu_LearningFromLabeledAndUnlabele.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2003_DavidMBlei_LatentDirichletAllocation.html b/stubs/2003_DavidMBlei_LatentDirichletAllocation.html
index 41db6cf0..5020c794 100644
--- a/stubs/2003_DavidMBlei_LatentDirichletAllocation.html
+++ b/stubs/2003_DavidMBlei_LatentDirichletAllocation.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2003_SeppHochreiter_GradientFlowInRecurrentNetsThe.html b/stubs/2003_SeppHochreiter_GradientFlowInRecurrentNetsThe.html
index 78e9b253..cfacfa68 100644
--- a/stubs/2003_SeppHochreiter_GradientFlowInRecurrentNetsThe.html
+++ b/stubs/2003_SeppHochreiter_GradientFlowInRecurrentNetsThe.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2003_WeiXu_DocumentClusteringBasedOnNonNe.html b/stubs/2003_WeiXu_DocumentClusteringBasedOnNonNe.html
index 91cdae7b..4e10702f 100644
--- a/stubs/2003_WeiXu_DocumentClusteringBasedOnNonNe.html
+++ b/stubs/2003_WeiXu_DocumentClusteringBasedOnNonNe.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2004_AaronClauset_FindingCommunityStructureInVer.html b/stubs/2004_AaronClauset_FindingCommunityStructureInVer.html
index 0afb8108..21bafade 100644
--- a/stubs/2004_AaronClauset_FindingCommunityStructureInVer.html
+++ b/stubs/2004_AaronClauset_FindingCommunityStructureInVer.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2005_CristianBucila_ModelCompression.html b/stubs/2005_CristianBucila_ModelCompression.html
index 2f8b2984..f18b1580 100644
--- a/stubs/2005_CristianBucila_ModelCompression.html
+++ b/stubs/2005_CristianBucila_ModelCompression.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2005_HuiZou_RegularizationAndVariableSelec.html b/stubs/2005_HuiZou_RegularizationAndVariableSelec.html
index 41c27188..7e998798 100644
--- a/stubs/2005_HuiZou_RegularizationAndVariableSelec.html
+++ b/stubs/2005_HuiZou_RegularizationAndVariableSelec.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2006_ArvindNarayanan_HowToBreakAnonymityOfTheNetfli.html b/stubs/2006_ArvindNarayanan_HowToBreakAnonymityOfTheNetfli.html
index b1973aee..c11c443d 100644
--- a/stubs/2006_ArvindNarayanan_HowToBreakAnonymityOfTheNetfli.html
+++ b/stubs/2006_ArvindNarayanan_HowToBreakAnonymityOfTheNetfli.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2006_GeoffHinton_ReducingTheDimensionalityOfDat.html b/stubs/2006_GeoffHinton_ReducingTheDimensionalityOfDat.html
index 6f066f66..89adeee1 100644
--- a/stubs/2006_GeoffHinton_ReducingTheDimensionalityOfDat.html
+++ b/stubs/2006_GeoffHinton_ReducingTheDimensionalityOfDat.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2007_OverviewOfTheContestAndDataset_TheNetflixPrize.html b/stubs/2007_OverviewOfTheContestAndDataset_TheNetflixPrize.html
index bf6b23d4..e25a6148 100644
--- a/stubs/2007_OverviewOfTheContestAndDataset_TheNetflixPrize.html
+++ b/stubs/2007_OverviewOfTheContestAndDataset_TheNetflixPrize.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2007_RobertMBell_TheBellkorSolutionToTheNetflix.html b/stubs/2007_RobertMBell_TheBellkorSolutionToTheNetflix.html
index e9ccc30a..8487a02d 100644
--- a/stubs/2007_RobertMBell_TheBellkorSolutionToTheNetflix.html
+++ b/stubs/2007_RobertMBell_TheBellkorSolutionToTheNetflix.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2008_AndreasToscher_TheBigchaosSolutionToTheNetfli.html b/stubs/2008_AndreasToscher_TheBigchaosSolutionToTheNetfli.html
index 7c2e6e2f..92edba98 100644
--- a/stubs/2008_AndreasToscher_TheBigchaosSolutionToTheNetfli.html
+++ b/stubs/2008_AndreasToscher_TheBigchaosSolutionToTheNetfli.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2008_LaurensVanDerMaaten_VisualizingDataUsingTSne.html b/stubs/2008_LaurensVanDerMaaten_VisualizingDataUsingTSne.html
index 6ac73b8c..59e692d1 100644
--- a/stubs/2008_LaurensVanDerMaaten_VisualizingDataUsingTSne.html
+++ b/stubs/2008_LaurensVanDerMaaten_VisualizingDataUsingTSne.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2008_RisiKondor_GroupTheoreticalMethodsInMachi.html b/stubs/2008_RisiKondor_GroupTheoreticalMethodsInMachi.html
index e6b165e8..140eda2e 100644
--- a/stubs/2008_RisiKondor_GroupTheoreticalMethodsInMachi.html
+++ b/stubs/2008_RisiKondor_GroupTheoreticalMethodsInMachi.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2008_RobertMBell_TheBellkor2008SolutionToTheNet.html b/stubs/2008_RobertMBell_TheBellkor2008SolutionToTheNet.html
index c08804e9..1d9b56a9 100644
--- a/stubs/2008_RobertMBell_TheBellkor2008SolutionToTheNet.html
+++ b/stubs/2008_RobertMBell_TheBellkor2008SolutionToTheNet.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2008_VincentDBlondel_FastUnfoldingOfCommunitiesInLa.html b/stubs/2008_VincentDBlondel_FastUnfoldingOfCommunitiesInLa.html
index 2b98a720..afd65db3 100644
--- a/stubs/2008_VincentDBlondel_FastUnfoldingOfCommunitiesInLa.html
+++ b/stubs/2008_VincentDBlondel_FastUnfoldingOfCommunitiesInLa.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2009_KilianWeinbergerAnirbanDasguptaJohnLangfordAlexSmolaJoshAttenberg_FeatureHashingForLargeScaleMul.html b/stubs/2009_KilianWeinbergerAnirbanDasguptaJohnLangfordAlexSmolaJoshAttenberg_FeatureHashingForLargeScaleMul.html
index 63a6287f..e1315733 100644
--- a/stubs/2009_KilianWeinbergerAnirbanDasguptaJohnLangfordAlexSmolaJoshAttenberg_FeatureHashingForLargeScaleMul.html
+++ b/stubs/2009_KilianWeinbergerAnirbanDasguptaJohnLangfordAlexSmolaJoshAttenberg_FeatureHashingForLargeScaleMul.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2009_NiranjanSrinivas_GaussianProcessOptimizationInT.html b/stubs/2009_NiranjanSrinivas_GaussianProcessOptimizationInT.html
index 3fdbec67..acdb68ae 100644
--- a/stubs/2009_NiranjanSrinivas_GaussianProcessOptimizationInT.html
+++ b/stubs/2009_NiranjanSrinivas_GaussianProcessOptimizationInT.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2010_MironBKursa_FeatureSelectionWithTheBorutaP.html b/stubs/2010_MironBKursa_FeatureSelectionWithTheBorutaP.html
index 4c9a52cf..57b73905 100644
--- a/stubs/2010_MironBKursa_FeatureSelectionWithTheBorutaP.html
+++ b/stubs/2010_MironBKursa_FeatureSelectionWithTheBorutaP.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2010_TomasMikolov_RecurrentNeuralNetworkBasedLan.html b/stubs/2010_TomasMikolov_RecurrentNeuralNetworkBasedLan.html
index 922beaab..2b7b9b4b 100644
--- a/stubs/2010_TomasMikolov_RecurrentNeuralNetworkBasedLan.html
+++ b/stubs/2010_TomasMikolov_RecurrentNeuralNetworkBasedLan.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2010_XavierGlorot_UnderstandingTheDifficultyOfTr.html b/stubs/2010_XavierGlorot_UnderstandingTheDifficultyOfTr.html
index 570ae60a..77f685f9 100644
--- a/stubs/2010_XavierGlorot_UnderstandingTheDifficultyOfTr.html
+++ b/stubs/2010_XavierGlorot_UnderstandingTheDifficultyOfTr.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2011_FengNiu_HogwildALockFreeApproachToPara.html b/stubs/2011_FengNiu_HogwildALockFreeApproachToPara.html
index d7aa78ef..f9790e53 100644
--- a/stubs/2011_FengNiu_HogwildALockFreeApproachToPara.html
+++ b/stubs/2011_FengNiu_HogwildALockFreeApproachToPara.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2011_XavierGlorot_DeepSparseRectifierNeuralNetwo.html b/stubs/2011_XavierGlorot_DeepSparseRectifierNeuralNetwo.html
index 41e3bcad..15255ea4 100644
--- a/stubs/2011_XavierGlorot_DeepSparseRectifierNeuralNetwo.html
+++ b/stubs/2011_XavierGlorot_DeepSparseRectifierNeuralNetwo.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2012_AlexKrizhevsky_UsingImagenetLeaderboardDateAr.html b/stubs/2012_AlexKrizhevsky_UsingImagenetLeaderboardDateAr.html
index 82ac2663..15198d3e 100644
--- a/stubs/2012_AlexKrizhevsky_UsingImagenetLeaderboardDateAr.html
+++ b/stubs/2012_AlexKrizhevsky_UsingImagenetLeaderboardDateAr.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2012_JamesBergstra_RandomSearchForHyperParameterO.html b/stubs/2012_JamesBergstra_RandomSearchForHyperParameterO.html
index 8d2a4c3c..40b7f5b3 100644
--- a/stubs/2012_JamesBergstra_RandomSearchForHyperParameterO.html
+++ b/stubs/2012_JamesBergstra_RandomSearchForHyperParameterO.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2012_NicholasChamandy_EstimatingUncertaintyForMassiv.html b/stubs/2012_NicholasChamandy_EstimatingUncertaintyForMassiv.html
index ad22ae26..3cf1cc88 100644
--- a/stubs/2012_NicholasChamandy_EstimatingUncertaintyForMassiv.html
+++ b/stubs/2012_NicholasChamandy_EstimatingUncertaintyForMassiv.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2013_DiederikPKingma_AutoEncodingVariationalBayes.html b/stubs/2013_DiederikPKingma_AutoEncodingVariationalBayes.html
index 00b92b3a..bf377f24 100644
--- a/stubs/2013_DiederikPKingma_AutoEncodingVariationalBayes.html
+++ b/stubs/2013_DiederikPKingma_AutoEncodingVariationalBayes.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2013_PierreBaldi_UnderstandingDropout.html b/stubs/2013_PierreBaldi_UnderstandingDropout.html
index 09123a9e..db75588f 100644
--- a/stubs/2013_PierreBaldi_UnderstandingDropout.html
+++ b/stubs/2013_PierreBaldi_UnderstandingDropout.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2013_TomasMikolov_DistributedRepresentationsOfWo.html b/stubs/2013_TomasMikolov_DistributedRepresentationsOfWo.html
index 4e63d1e0..0636f469 100644
--- a/stubs/2013_TomasMikolov_DistributedRepresentationsOfWo.html
+++ b/stubs/2013_TomasMikolov_DistributedRepresentationsOfWo.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2013_VolodymyrMnih_DqnPlayingAtariWithDeepReinfor.html b/stubs/2013_VolodymyrMnih_DqnPlayingAtariWithDeepReinfor.html
index 5f1708d0..6546b711 100644
--- a/stubs/2013_VolodymyrMnih_DqnPlayingAtariWithDeepReinfor.html
+++ b/stubs/2013_VolodymyrMnih_DqnPlayingAtariWithDeepReinfor.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014_AlexGraves_GeneratingSequencesWithRecurre.html b/stubs/2014_AlexGraves_GeneratingSequencesWithRecurre.html
index 5d17dbcf..270bb957 100644
--- a/stubs/2014_AlexGraves_GeneratingSequencesWithRecurre.html
+++ b/stubs/2014_AlexGraves_GeneratingSequencesWithRecurre.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014_AnhNguyen_DeepNeuralNetworksAreEasilyFoo.html b/stubs/2014_AnhNguyen_DeepNeuralNetworksAreEasilyFoo.html
index 1628ec0e..a22c376a 100644
--- a/stubs/2014_AnhNguyen_DeepNeuralNetworksAreEasilyFoo.html
+++ b/stubs/2014_AnhNguyen_DeepNeuralNetworksAreEasilyFoo.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014_AravindhMahendran_UnderstandingDeepImageRepresen.html b/stubs/2014_AravindhMahendran_UnderstandingDeepImageRepresen.html
index 1bfd1b01..3db56510 100644
--- a/stubs/2014_AravindhMahendran_UnderstandingDeepImageRepresen.html
+++ b/stubs/2014_AravindhMahendran_UnderstandingDeepImageRepresen.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014_DiederikPKingma_AdamAMethodForStochasticOptimi.html b/stubs/2014_DiederikPKingma_AdamAMethodForStochasticOptimi.html
index 50d8f6fb..a9805c31 100644
--- a/stubs/2014_DiederikPKingma_AdamAMethodForStochasticOptimi.html
+++ b/stubs/2014_DiederikPKingma_AdamAMethodForStochasticOptimi.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014_DzmitryBahdanau_NeuralMachineTranslationByJoin.html b/stubs/2014_DzmitryBahdanau_NeuralMachineTranslationByJoin.html
index dbc52fcf..fd6150c8 100644
--- a/stubs/2014_DzmitryBahdanau_NeuralMachineTranslationByJoin.html
+++ b/stubs/2014_DzmitryBahdanau_NeuralMachineTranslationByJoin.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014_IlyaSutskever_SequenceToSequenceLearningWith.html b/stubs/2014_IlyaSutskever_SequenceToSequenceLearningWith.html
index 64da7180..cb700daa 100644
--- a/stubs/2014_IlyaSutskever_SequenceToSequenceLearningWith.html
+++ b/stubs/2014_IlyaSutskever_SequenceToSequenceLearningWith.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014_KarenSimonyan_VeryDeepConvolutionalNetworksF.html b/stubs/2014_KarenSimonyan_VeryDeepConvolutionalNetworksF.html
index 1a1eaed5..be6781b6 100644
--- a/stubs/2014_KarenSimonyan_VeryDeepConvolutionalNetworksF.html
+++ b/stubs/2014_KarenSimonyan_VeryDeepConvolutionalNetworksF.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014_NitishSrivastava_DropoutASimpleWayToPreventNeur.html b/stubs/2014_NitishSrivastava_DropoutASimpleWayToPreventNeur.html
index 87f28d1d..899a5f47 100644
--- a/stubs/2014_NitishSrivastava_DropoutASimpleWayToPreventNeur.html
+++ b/stubs/2014_NitishSrivastava_DropoutASimpleWayToPreventNeur.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014_OmerLevy_NeuralWordEmbeddingAsImplicitM.html b/stubs/2014_OmerLevy_NeuralWordEmbeddingAsImplicitM.html
index 4b038bf2..c35613b5 100644
--- a/stubs/2014_OmerLevy_NeuralWordEmbeddingAsImplicitM.html
+++ b/stubs/2014_OmerLevy_NeuralWordEmbeddingAsImplicitM.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014_YannDauphin_IdentifyingAndAttackingTheSadd.html b/stubs/2014_YannDauphin_IdentifyingAndAttackingTheSadd.html
index 89396cb6..f20726bd 100644
--- a/stubs/2014_YannDauphin_IdentifyingAndAttackingTheSadd.html
+++ b/stubs/2014_YannDauphin_IdentifyingAndAttackingTheSadd.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014_YiHsuanTsai_LocalityPreservingHashing.html b/stubs/2014_YiHsuanTsai_LocalityPreservingHashing.html
index b6e7c984..4ad6513c 100644
--- a/stubs/2014_YiHsuanTsai_LocalityPreservingHashing.html
+++ b/stubs/2014_YiHsuanTsai_LocalityPreservingHashing.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2014__OnThePropertiesOfNeuralMachine.html b/stubs/2014__OnThePropertiesOfNeuralMachine.html
index 4a39b440..0feb0c84 100644
--- a/stubs/2014__OnThePropertiesOfNeuralMachine.html
+++ b/stubs/2014__OnThePropertiesOfNeuralMachine.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_AlexanderMordvintsev_InceptionismGoingDeeperIntoNeu.html b/stubs/2015_AlexanderMordvintsev_InceptionismGoingDeeperIntoNeu.html
index 2b39c4e8..4e776f09 100644
--- a/stubs/2015_AlexanderMordvintsev_InceptionismGoingDeeperIntoNeu.html
+++ b/stubs/2015_AlexanderMordvintsev_InceptionismGoingDeeperIntoNeu.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_DSculley_HiddenTechnicalDebtInMachineLe.html b/stubs/2015_DSculley_HiddenTechnicalDebtInMachineLe.html
index bbf32de9..4025df65 100644
--- a/stubs/2015_DSculley_HiddenTechnicalDebtInMachineLe.html
+++ b/stubs/2015_DSculley_HiddenTechnicalDebtInMachineLe.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_GeoffreyHinton_DistillingTheKnowledgeInANeura.html b/stubs/2015_GeoffreyHinton_DistillingTheKnowledgeInANeura.html
index fd2b3883..bf593f94 100644
--- a/stubs/2015_GeoffreyHinton_DistillingTheKnowledgeInANeura.html
+++ b/stubs/2015_GeoffreyHinton_DistillingTheKnowledgeInANeura.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_GregoryKoch_SiameseNeuralNetworksForOneSho.html b/stubs/2015_GregoryKoch_SiameseNeuralNetworksForOneSho.html
index 6348634c..cbe6491a 100644
--- a/stubs/2015_GregoryKoch_SiameseNeuralNetworksForOneSho.html
+++ b/stubs/2015_GregoryKoch_SiameseNeuralNetworksForOneSho.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_JaschaSohlDickstein_DeepUnsupervisedLearningUsingN.html b/stubs/2015_JaschaSohlDickstein_DeepUnsupervisedLearningUsingN.html
index 2d467ba6..1646a953 100644
--- a/stubs/2015_JaschaSohlDickstein_DeepUnsupervisedLearningUsingN.html
+++ b/stubs/2015_JaschaSohlDickstein_DeepUnsupervisedLearningUsingN.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_KaimingHe_DeepResidualLearningForImageRe.html b/stubs/2015_KaimingHe_DeepResidualLearningForImageRe.html
index 8e2ccd37..cb7dc78e 100644
--- a/stubs/2015_KaimingHe_DeepResidualLearningForImageRe.html
+++ b/stubs/2015_KaimingHe_DeepResidualLearningForImageRe.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_NaftaliTishby_DeepLearningAndTheInformationB.html b/stubs/2015_NaftaliTishby_DeepLearningAndTheInformationB.html
index 392b3a66..06fe0911 100644
--- a/stubs/2015_NaftaliTishby_DeepLearningAndTheInformationB.html
+++ b/stubs/2015_NaftaliTishby_DeepLearningAndTheInformationB.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_RicoSennrich_NeuralMachineTranslationOfRare.html b/stubs/2015_RicoSennrich_NeuralMachineTranslationOfRare.html
index 5a5573bd..e59e9514 100644
--- a/stubs/2015_RicoSennrich_NeuralMachineTranslationOfRare.html
+++ b/stubs/2015_RicoSennrich_NeuralMachineTranslationOfRare.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_RupeshKumarSrivastava_HighwayNetworks.html b/stubs/2015_RupeshKumarSrivastava_HighwayNetworks.html
index e6d32709..161c4b7d 100644
--- a/stubs/2015_RupeshKumarSrivastava_HighwayNetworks.html
+++ b/stubs/2015_RupeshKumarSrivastava_HighwayNetworks.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_SergeyIoffe_BatchNormalizationAccelerating.html b/stubs/2015_SergeyIoffe_BatchNormalizationAccelerating.html
index 55d30ce8..1193d560 100644
--- a/stubs/2015_SergeyIoffe_BatchNormalizationAccelerating.html
+++ b/stubs/2015_SergeyIoffe_BatchNormalizationAccelerating.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_VolodymyrMnih_HumanLevelControlThroughDeepRe.html b/stubs/2015_VolodymyrMnih_HumanLevelControlThroughDeepRe.html
index 78cd07ff..e7358234 100644
--- a/stubs/2015_VolodymyrMnih_HumanLevelControlThroughDeepRe.html
+++ b/stubs/2015_VolodymyrMnih_HumanLevelControlThroughDeepRe.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2015_YarinGal_DropoutAsABayesianApproximatio.html b/stubs/2015_YarinGal_DropoutAsABayesianApproximatio.html
index 2290eef0..b334e3e3 100644
--- a/stubs/2015_YarinGal_DropoutAsABayesianApproximatio.html
+++ b/stubs/2015_YarinGal_DropoutAsABayesianApproximatio.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2016_AaronVanDenOord_WavenetAGenerativeModelForRawA.html b/stubs/2016_AaronVanDenOord_WavenetAGenerativeModelForRawA.html
index 8bf72118..e8f5b4df 100644
--- a/stubs/2016_AaronVanDenOord_WavenetAGenerativeModelForRawA.html
+++ b/stubs/2016_AaronVanDenOord_WavenetAGenerativeModelForRawA.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2016_ChiyuanZhang_UnderstandingDeepLearningRequi.html b/stubs/2016_ChiyuanZhang_UnderstandingDeepLearningRequi.html
index d2ce48fb..2f77e0e2 100644
--- a/stubs/2016_ChiyuanZhang_UnderstandingDeepLearningRequi.html
+++ b/stubs/2016_ChiyuanZhang_UnderstandingDeepLearningRequi.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2016_DanHendrycks_GaussianErrorLinearUnitsGelus.html b/stubs/2016_DanHendrycks_GaussianErrorLinearUnitsGelus.html
index 78f426c3..252976f9 100644
--- a/stubs/2016_DanHendrycks_GaussianErrorLinearUnitsGelus.html
+++ b/stubs/2016_DanHendrycks_GaussianErrorLinearUnitsGelus.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2016_EricJang_CategoricalReparameterizationW.html b/stubs/2016_EricJang_CategoricalReparameterizationW.html
index b00cdf05..659ee82d 100644
--- a/stubs/2016_EricJang_CategoricalReparameterizationW.html
+++ b/stubs/2016_EricJang_CategoricalReparameterizationW.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2016_ManuelRuder_ArtisticStyleTransferForVideos.html b/stubs/2016_ManuelRuder_ArtisticStyleTransferForVideos.html
index 3aa98667..7a3f3568 100644
--- a/stubs/2016_ManuelRuder_ArtisticStyleTransferForVideos.html
+++ b/stubs/2016_ManuelRuder_ArtisticStyleTransferForVideos.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2016_TianqiChen_XgboostAScalableTreeBoostingSy.html b/stubs/2016_TianqiChen_XgboostAScalableTreeBoostingSy.html
index bfdd221a..412a5fa3 100644
--- a/stubs/2016_TianqiChen_XgboostAScalableTreeBoostingSy.html
+++ b/stubs/2016_TianqiChen_XgboostAScalableTreeBoostingSy.html
@@ -315,6 +315,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2016_TsungYiLin_FeaturePyramidNetworksForObjec.html b/stubs/2016_TsungYiLin_FeaturePyramidNetworksForObjec.html
index fe17a152..df9fdc09 100644
--- a/stubs/2016_TsungYiLin_FeaturePyramidNetworksForObjec.html
+++ b/stubs/2016_TsungYiLin_FeaturePyramidNetworksForObjec.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2016_VictorChernozhukov_DoubleDebiasedMachineLearningF.html b/stubs/2016_VictorChernozhukov_DoubleDebiasedMachineLearningF.html
index 2e76eb4b..5b751540 100644
--- a/stubs/2016_VictorChernozhukov_DoubleDebiasedMachineLearningF.html
+++ b/stubs/2016_VictorChernozhukov_DoubleDebiasedMachineLearningF.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2016_YonghuiWu_GoogleSNeuralMachineTranslatio.html b/stubs/2016_YonghuiWu_GoogleSNeuralMachineTranslatio.html
index ff43fe4c..8956ba11 100644
--- a/stubs/2016_YonghuiWu_GoogleSNeuralMachineTranslatio.html
+++ b/stubs/2016_YonghuiWu_GoogleSNeuralMachineTranslatio.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2016__HyperbandANovelBanditBasedAppr.html b/stubs/2016__HyperbandANovelBanditBasedAppr.html
index d8896d33..76365d03 100644
--- a/stubs/2016__HyperbandANovelBanditBasedAppr.html
+++ b/stubs/2016__HyperbandANovelBanditBasedAppr.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_AaronVanDenOord_NeuralDiscreteRepresentationLe.html b/stubs/2017_AaronVanDenOord_NeuralDiscreteRepresentationLe.html
index 081e1053..db779d09 100644
--- a/stubs/2017_AaronVanDenOord_NeuralDiscreteRepresentationLe.html
+++ b/stubs/2017_AaronVanDenOord_NeuralDiscreteRepresentationLe.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_AmazonRuofengWen_AMultiHorizonQuantileRecurrent.html b/stubs/2017_AmazonRuofengWen_AMultiHorizonQuantileRecurrent.html
index 0be87901..b35f40c8 100644
--- a/stubs/2017_AmazonRuofengWen_AMultiHorizonQuantileRecurrent.html
+++ b/stubs/2017_AmazonRuofengWen_AMultiHorizonQuantileRecurrent.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_AndrewBrock_SmashOneShotModelArchitectureS.html b/stubs/2017_AndrewBrock_SmashOneShotModelArchitectureS.html
index 07582589..c61c1216 100644
--- a/stubs/2017_AndrewBrock_SmashOneShotModelArchitectureS.html
+++ b/stubs/2017_AndrewBrock_SmashOneShotModelArchitectureS.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_AndrewGHoward_MobilenetsEfficientConvolution.html b/stubs/2017_AndrewGHoward_MobilenetsEfficientConvolution.html
index 4f490a74..d3fd6698 100644
--- a/stubs/2017_AndrewGHoward_MobilenetsEfficientConvolution.html
+++ b/stubs/2017_AndrewGHoward_MobilenetsEfficientConvolution.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_AshishVaswani_AttentionIsAllYouNeed.html b/stubs/2017_AshishVaswani_AttentionIsAllYouNeed.html
index 8cfc3804..ca88a81e 100644
--- a/stubs/2017_AshishVaswani_AttentionIsAllYouNeed.html
+++ b/stubs/2017_AshishVaswani_AttentionIsAllYouNeed.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_BolinGao_OnThePropertiesOfTheSoftmaxFun.html b/stubs/2017_BolinGao_OnThePropertiesOfTheSoftmaxFun.html
index cb97906d..9aeda006 100644
--- a/stubs/2017_BolinGao_OnThePropertiesOfTheSoftmaxFun.html
+++ b/stubs/2017_BolinGao_OnThePropertiesOfTheSoftmaxFun.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_ChuanGuo_OnCalibrationOfModernNeuralNet.html b/stubs/2017_ChuanGuo_OnCalibrationOfModernNeuralNet.html
index a5ce9957..aa31128e 100644
--- a/stubs/2017_ChuanGuo_OnCalibrationOfModernNeuralNet.html
+++ b/stubs/2017_ChuanGuo_OnCalibrationOfModernNeuralNet.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_JieHu_SqueezeAndExcitationNetworks.html b/stubs/2017_JieHu_SqueezeAndExcitationNetworks.html
index d935efc7..8357be33 100644
--- a/stubs/2017_JieHu_SqueezeAndExcitationNetworks.html
+++ b/stubs/2017_JieHu_SqueezeAndExcitationNetworks.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_JohnSchulman_ProximalPolicyOptimizationAlgo.html b/stubs/2017_JohnSchulman_ProximalPolicyOptimizationAlgo.html
index fa7fb22e..5593f818 100644
--- a/stubs/2017_JohnSchulman_ProximalPolicyOptimizationAlgo.html
+++ b/stubs/2017_JohnSchulman_ProximalPolicyOptimizationAlgo.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_KaimingHe_MaskRCnn.html b/stubs/2017_KaimingHe_MaskRCnn.html
index 2f614176..961e9f34 100644
--- a/stubs/2017_KaimingHe_MaskRCnn.html
+++ b/stubs/2017_KaimingHe_MaskRCnn.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_KazuyukiHara_AnalysisOfDropoutLearningRegar.html b/stubs/2017_KazuyukiHara_AnalysisOfDropoutLearningRegar.html
index a91e0b38..41bc684a 100644
--- a/stubs/2017_KazuyukiHara_AnalysisOfDropoutLearningRegar.html
+++ b/stubs/2017_KazuyukiHara_AnalysisOfDropoutLearningRegar.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_MartinHeusel_GansTrainedByATwoTimeScaleUpda.html b/stubs/2017_MartinHeusel_GansTrainedByATwoTimeScaleUpda.html
index 242c1ba0..bd7316c8 100644
--- a/stubs/2017_MartinHeusel_GansTrainedByATwoTimeScaleUpda.html
+++ b/stubs/2017_MartinHeusel_GansTrainedByATwoTimeScaleUpda.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_StephanMandt_StochasticGradientDescentAsApp.html b/stubs/2017_StephanMandt_StochasticGradientDescentAsApp.html
index 72d08885..a38bfc84 100644
--- a/stubs/2017_StephanMandt_StochasticGradientDescentAsApp.html
+++ b/stubs/2017_StephanMandt_StochasticGradientDescentAsApp.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_XunHuang_ArbitraryStyleTransferInRealTi.html b/stubs/2017_XunHuang_ArbitraryStyleTransferInRealTi.html
index 7e970631..b3dfef53 100644
--- a/stubs/2017_XunHuang_ArbitraryStyleTransferInRealTi.html
+++ b/stubs/2017_XunHuang_ArbitraryStyleTransferInRealTi.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2017_ZhouhanLin_AStructuredSelfAttentiveSenten.html b/stubs/2017_ZhouhanLin_AStructuredSelfAttentiveSenten.html
index f0d8dad1..373fabc0 100644
--- a/stubs/2017_ZhouhanLin_AStructuredSelfAttentiveSenten.html
+++ b/stubs/2017_ZhouhanLin_AStructuredSelfAttentiveSenten.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_AaronVanDenOord_RepresentationLearningWithCont.html b/stubs/2018_AaronVanDenOord_RepresentationLearningWithCont.html
index da038a27..d9d8de0c 100644
--- a/stubs/2018_AaronVanDenOord_RepresentationLearningWithCont.html
+++ b/stubs/2018_AaronVanDenOord_RepresentationLearningWithCont.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_ArthurJacot_NeuralTangentKernelConvergence.html b/stubs/2018_ArthurJacot_NeuralTangentKernelConvergence.html
index 643bbb50..328e1e8a 100644
--- a/stubs/2018_ArthurJacot_NeuralTangentKernelConvergence.html
+++ b/stubs/2018_ArthurJacot_NeuralTangentKernelConvergence.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_CarlVondrick_TrackingEmergesByColorizingVid.html b/stubs/2018_CarlVondrick_TrackingEmergesByColorizingVid.html
index 59d9d174..ac4b6484 100644
--- a/stubs/2018_CarlVondrick_TrackingEmergesByColorizingVid.html
+++ b/stubs/2018_CarlVondrick_TrackingEmergesByColorizingVid.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_DmitryUlyanov_DeepImagePrior.html b/stubs/2018_DmitryUlyanov_DeepImagePrior.html
index 86c19c67..67c0966f 100644
--- a/stubs/2018_DmitryUlyanov_DeepImagePrior.html
+++ b/stubs/2018_DmitryUlyanov_DeepImagePrior.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_JacobDevlin_BertPreTrainingOfDeepBidirecti.html b/stubs/2018_JacobDevlin_BertPreTrainingOfDeepBidirecti.html
index b529e5ce..ed55c403 100644
--- a/stubs/2018_JacobDevlin_BertPreTrainingOfDeepBidirecti.html
+++ b/stubs/2018_JacobDevlin_BertPreTrainingOfDeepBidirecti.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_JonathanFrankle_TheLotteryTicketHypothesisFind.html b/stubs/2018_JonathanFrankle_TheLotteryTicketHypothesisFind.html
index 68ec5c15..0e6796d4 100644
--- a/stubs/2018_JonathanFrankle_TheLotteryTicketHypothesisFind.html
+++ b/stubs/2018_JonathanFrankle_TheLotteryTicketHypothesisFind.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_LarsMescheder_OccupancyNetworksLearning3DRec.html b/stubs/2018_LarsMescheder_OccupancyNetworksLearning3DRec.html
index 7ce9ea4f..40fa64d1 100644
--- a/stubs/2018_LarsMescheder_OccupancyNetworksLearning3DRec.html
+++ b/stubs/2018_LarsMescheder_OccupancyNetworksLearning3DRec.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_LelandMcinnes_UmapUniformManifoldApproximati.html b/stubs/2018_LelandMcinnes_UmapUniformManifoldApproximati.html
index 27614da7..edb42150 100644
--- a/stubs/2018_LelandMcinnes_UmapUniformManifoldApproximati.html
+++ b/stubs/2018_LelandMcinnes_UmapUniformManifoldApproximati.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_MarkSandler_Mobilenetv2InvertedResidualsAn.html b/stubs/2018_MarkSandler_Mobilenetv2InvertedResidualsAn.html
index 42421f5a..1d0014d5 100644
--- a/stubs/2018_MarkSandler_Mobilenetv2InvertedResidualsAn.html
+++ b/stubs/2018_MarkSandler_Mobilenetv2InvertedResidualsAn.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_PeterWBattaglia_RelationalInductiveBiasesDeepL.html b/stubs/2018_PeterWBattaglia_RelationalInductiveBiasesDeepL.html
index 63cfae8a..60795aa2 100644
--- a/stubs/2018_PeterWBattaglia_RelationalInductiveBiasesDeepL.html
+++ b/stubs/2018_PeterWBattaglia_RelationalInductiveBiasesDeepL.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_RandallBalestrieroRichardGBaraniuk_ASplineTheoryOfDeepNetworks.html b/stubs/2018_RandallBalestrieroRichardGBaraniuk_ASplineTheoryOfDeepNetworks.html
index 52242191..d3d2a776 100644
--- a/stubs/2018_RandallBalestrieroRichardGBaraniuk_ASplineTheoryOfDeepNetworks.html
+++ b/stubs/2018_RandallBalestrieroRichardGBaraniuk_ASplineTheoryOfDeepNetworks.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2018_XiangLi_UnderstandingTheDisharmonyBetw.html b/stubs/2018_XiangLi_UnderstandingTheDisharmonyBetw.html
index af40a8ce..4e20623c 100644
--- a/stubs/2018_XiangLi_UnderstandingTheDisharmonyBetw.html
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@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2019_AliRazavi_GeneratingDiverseHighFidelityI.html b/stubs/2019_AliRazavi_GeneratingDiverseHighFidelityI.html
index ac06e8b5..6ee8c664 100644
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+++ b/stubs/2019_AliRazavi_GeneratingDiverseHighFidelityI.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2019_FrancoisChollet_OnTheMeasureOfIntelligence.html b/stubs/2019_FrancoisChollet_OnTheMeasureOfIntelligence.html
index b96f4cdb..e24c3bef 100644
--- a/stubs/2019_FrancoisChollet_OnTheMeasureOfIntelligence.html
+++ b/stubs/2019_FrancoisChollet_OnTheMeasureOfIntelligence.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2019_MikhailBelkin_ReconcilingModernMachineLearni.html b/stubs/2019_MikhailBelkin_ReconcilingModernMachineLearni.html
index c5133192..6aff69b3 100644
--- a/stubs/2019_MikhailBelkin_ReconcilingModernMachineLearni.html
+++ b/stubs/2019_MikhailBelkin_ReconcilingModernMachineLearni.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2019_MingxingTan_EfficientnetRethinkingModelSca.html b/stubs/2019_MingxingTan_EfficientnetRethinkingModelSca.html
index 74019610..c107fc83 100644
--- a/stubs/2019_MingxingTan_EfficientnetRethinkingModelSca.html
+++ b/stubs/2019_MingxingTan_EfficientnetRethinkingModelSca.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2 current active"><a class="current reference internal" href="#">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2019_OferMShir_OnTheCovarianceHessianRelation.html b/stubs/2019_OferMShir_OnTheCovarianceHessianRelation.html
index f10a2ad7..299e1b5a 100644
--- a/stubs/2019_OferMShir_OnTheCovarianceHessianRelation.html
+++ b/stubs/2019_OferMShir_OnTheCovarianceHessianRelation.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2 current active"><a class="current reference internal" href="#">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html b/stubs/2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html
index caa275ef..cc538264 100644
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+    <link rel="next" title="“The Bitter Lesson”" href="2019_RichSutton_TheBitterLesson.html" />
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 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2 current active"><a class="current reference internal" href="#">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
@@ -595,11 +596,11 @@ <h1>“Deep Double Descent: Where Bigger Models and More Data Hurt”<a class="h
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+<li class="toctree-l2"><a class="reference internal" href="1967_TMCover_NearestNeighborPatternClassifi.html">“Nearest Neighbor Pattern Classification”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="1971_VVapnikAndAChervonenkis_OnTheUniformConvergenceOfRelat.html">“On the uniform convergence of relative frequencies of events to their probabilities”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="1979_BradleyEffron_BootstrapMethodsAnotherLookAtT.html">“Bootstrap Methods: Another Look at the Jackknife”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="1980_TomMitchell_TheNeedForBiasesInLearningGene.html">“The need for biases in learning generalizations”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="1982_TeuvoKohonen_SelfOrganizedFormationOfTopolo.html">“Self-Organized Formation of Topologically Correct Feature Maps”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="1984_BreimanL_CartClassificationAndRegressio.html">CART) “Classification and Regression Trees” - in lieu of the book, here’s a [topic summary from 2011</a></li>
+<li class="toctree-l2"><a class="reference internal" href="1984_LGValiant_ATheoryOfTheLearnable.html">“A Theory of the Learnable”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="1984_WilliamBJohnson_ExtensionsOfLipschitzMappingsI.html">“Extensions_of_Lipschitz_mappings_into_a_Hilbert_space”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="1986_DavidRumelhart_LearningRepresentationsByBackP.html">“Learning representations by back-propagating errors”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="1986_JRQuinlan_Id3InductionOfDecisionTrees.html">ID3) [“Induction of Decision Trees”</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="1988_ScottDeerwester_IndexingByLatentSemanticAnalys.html">“Indexing by Latent Semantic Analysis”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="1989_Blumer_LearnabilityAndTheVapnikChervo.html">“Learnability and the Vapnik-Chervonenkis Dimension “</a></li>
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diff --git a/stubs/2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html b/stubs/2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html
index 2e107a7a..bd6a94cb 100644
--- a/stubs/2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html
+++ b/stubs/2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html
@@ -66,7 +66,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2 current active"><a class="current reference internal" href="#">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
@@ -586,12 +587,12 @@ <h1>“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”<a
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+        <p class="prev-next-title">“The Bitter Lesson”</p>
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diff --git a/stubs/2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html b/stubs/2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html
index 9a2ed546..6ec86aa9 100644
--- a/stubs/2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html
+++ b/stubs/2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2 current active"><a class="current reference internal" href="#">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2020_AndrewGelman_BayesianWorkflow.html b/stubs/2020_AndrewGelman_BayesianWorkflow.html
index e345c4e3..2415f0de 100644
--- a/stubs/2020_AndrewGelman_BayesianWorkflow.html
+++ b/stubs/2020_AndrewGelman_BayesianWorkflow.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2 current active"><a class="current reference internal" href="#">“Bayesian workflow”</a></li>
diff --git a/stubs/2020_ArmenAghajanyan_IntrinsicDimensionalityExplain.html b/stubs/2020_ArmenAghajanyan_IntrinsicDimensionalityExplain.html
index 5311924b..75164240 100644
--- a/stubs/2020_ArmenAghajanyan_IntrinsicDimensionalityExplain.html
+++ b/stubs/2020_ArmenAghajanyan_IntrinsicDimensionalityExplain.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2020_BenMildenhall_NerfRepresentingScenesAsNeural.html b/stubs/2020_BenMildenhall_NerfRepresentingScenesAsNeural.html
index 7fdd0061..c91ae57e 100644
--- a/stubs/2020_BenMildenhall_NerfRepresentingScenesAsNeural.html
+++ b/stubs/2020_BenMildenhall_NerfRepresentingScenesAsNeural.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2020_JonathanHo_DenoisingDiffusionProbabilisti.html b/stubs/2020_JonathanHo_DenoisingDiffusionProbabilisti.html
index f8d7dc27..f0e84697 100644
--- a/stubs/2020_JonathanHo_DenoisingDiffusionProbabilisti.html
+++ b/stubs/2020_JonathanHo_DenoisingDiffusionProbabilisti.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2020_PatrickEsser_TamingTransformersForHighResol.html b/stubs/2020_PatrickEsser_TamingTransformersForHighResol.html
index d53be50d..88fc0a39 100644
--- a/stubs/2020_PatrickEsser_TamingTransformersForHighResol.html
+++ b/stubs/2020_PatrickEsser_TamingTransformersForHighResol.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2020_SongMei_TheGeneralizationErrorOfRandom.html b/stubs/2020_SongMei_TheGeneralizationErrorOfRandom.html
index f67b5e40..0767b15d 100644
--- a/stubs/2020_SongMei_TheGeneralizationErrorOfRandom.html
+++ b/stubs/2020_SongMei_TheGeneralizationErrorOfRandom.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2020_TomBBrown_LanguageModelsAreFewShotLearne.html b/stubs/2020_TomBBrown_LanguageModelsAreFewShotLearne.html
index 78cb45ba..616e550b 100644
--- a/stubs/2020_TomBBrown_LanguageModelsAreFewShotLearne.html
+++ b/stubs/2020_TomBBrown_LanguageModelsAreFewShotLearne.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2020_VincentSitzmann_ImplicitNeuralRepresentationsW.html b/stubs/2020_VincentSitzmann_ImplicitNeuralRepresentationsW.html
index 513e9d73..2652e3fb 100644
--- a/stubs/2020_VincentSitzmann_ImplicitNeuralRepresentationsW.html
+++ b/stubs/2020_VincentSitzmann_ImplicitNeuralRepresentationsW.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2021_AlecRadford_LearningTransferableVisualMode.html b/stubs/2021_AlecRadford_LearningTransferableVisualMode.html
index addff49d..158a38a6 100644
--- a/stubs/2021_AlecRadford_LearningTransferableVisualMode.html
+++ b/stubs/2021_AlecRadford_LearningTransferableVisualMode.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2021_AletheaPower_GrokkingGeneralizationBeyondOv.html b/stubs/2021_AletheaPower_GrokkingGeneralizationBeyondOv.html
index 305099c1..28d2768c 100644
--- a/stubs/2021_AletheaPower_GrokkingGeneralizationBeyondOv.html
+++ b/stubs/2021_AletheaPower_GrokkingGeneralizationBeyondOv.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2021_CasperBenjaminFreksen_AnIntroductionToJohnsonLindens.html b/stubs/2021_CasperBenjaminFreksen_AnIntroductionToJohnsonLindens.html
index da8a8daa..225ca2b4 100644
--- a/stubs/2021_CasperBenjaminFreksen_AnIntroductionToJohnsonLindens.html
+++ b/stubs/2021_CasperBenjaminFreksen_AnIntroductionToJohnsonLindens.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2021_ChenlinMeng_SdeditGuidedImageSynthesisAndE.html b/stubs/2021_ChenlinMeng_SdeditGuidedImageSynthesisAndE.html
index d2018183..8ec3c379 100644
--- a/stubs/2021_ChenlinMeng_SdeditGuidedImageSynthesisAndE.html
+++ b/stubs/2021_ChenlinMeng_SdeditGuidedImageSynthesisAndE.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2021_EdwardJHu_LoraLowRankAdaptationOfLargeLa.html b/stubs/2021_EdwardJHu_LoraLowRankAdaptationOfLargeLa.html
index 934f2032..c359f167 100644
--- a/stubs/2021_EdwardJHu_LoraLowRankAdaptationOfLargeLa.html
+++ b/stubs/2021_EdwardJHu_LoraLowRankAdaptationOfLargeLa.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2021_JohnJumper_HighlyAccurateProteinStructure.html b/stubs/2021_JohnJumper_HighlyAccurateProteinStructure.html
index d94c9252..51e5642a 100644
--- a/stubs/2021_JohnJumper_HighlyAccurateProteinStructure.html
+++ b/stubs/2021_JohnJumper_HighlyAccurateProteinStructure.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2021_JonathanHo_ClassifierFreeDiffusionGuidanc.html b/stubs/2021_JonathanHo_ClassifierFreeDiffusionGuidanc.html
index 0b878304..70f1a447 100644
--- a/stubs/2021_JonathanHo_ClassifierFreeDiffusionGuidanc.html
+++ b/stubs/2021_JonathanHo_ClassifierFreeDiffusionGuidanc.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2021_MathildeCaron_EmergingPropertiesInSelfSuperv.html b/stubs/2021_MathildeCaron_EmergingPropertiesInSelfSuperv.html
index 8bd343d7..d37f9739 100644
--- a/stubs/2021_MathildeCaron_EmergingPropertiesInSelfSuperv.html
+++ b/stubs/2021_MathildeCaron_EmergingPropertiesInSelfSuperv.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2021_MichaelMBronstein_GeometricDeepLearningGridsGrou.html b/stubs/2021_MichaelMBronstein_GeometricDeepLearningGridsGrou.html
index b79ba505..25d9fe58 100644
--- a/stubs/2021_MichaelMBronstein_GeometricDeepLearningGridsGrou.html
+++ b/stubs/2021_MichaelMBronstein_GeometricDeepLearningGridsGrou.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2021_RandallBalestriero_LearningInHighDimensionAlwaysA.html b/stubs/2021_RandallBalestriero_LearningInHighDimensionAlwaysA.html
index c9e5f997..12edff28 100644
--- a/stubs/2021_RandallBalestriero_LearningInHighDimensionAlwaysA.html
+++ b/stubs/2021_RandallBalestriero_LearningInHighDimensionAlwaysA.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2021_YehudaDar_AFarewellToTheBiasVarianceTrad.html b/stubs/2021_YehudaDar_AFarewellToTheBiasVarianceTrad.html
index 43042e6a..0fb9d585 100644
--- a/stubs/2021_YehudaDar_AFarewellToTheBiasVarianceTrad.html
+++ b/stubs/2021_YehudaDar_AFarewellToTheBiasVarianceTrad.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2022_ArpitBansal_ColdDiffusionInvertingArbitrar.html b/stubs/2022_ArpitBansal_ColdDiffusionInvertingArbitrar.html
index df705f22..d06b9c13 100644
--- a/stubs/2022_ArpitBansal_ColdDiffusionInvertingArbitrar.html
+++ b/stubs/2022_ArpitBansal_ColdDiffusionInvertingArbitrar.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2022_BenPoole_DreamfusionTextTo3DUsing2DDiff.html b/stubs/2022_BenPoole_DreamfusionTextTo3DUsing2DDiff.html
index b6db4c06..fd48f1dc 100644
--- a/stubs/2022_BenPoole_DreamfusionTextTo3DUsing2DDiff.html
+++ b/stubs/2022_BenPoole_DreamfusionTextTo3DUsing2DDiff.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2022_JasonWei_ChainOfThoughtPromptingElicits.html b/stubs/2022_JasonWei_ChainOfThoughtPromptingElicits.html
index 96127434..dba2dbcd 100644
--- a/stubs/2022_JasonWei_ChainOfThoughtPromptingElicits.html
+++ b/stubs/2022_JasonWei_ChainOfThoughtPromptingElicits.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2022_JordanHoffmann_TrainingComputeOptimalLargeLan.html b/stubs/2022_JordanHoffmann_TrainingComputeOptimalLargeLan.html
index 49472ad8..dc271ae7 100644
--- a/stubs/2022_JordanHoffmann_TrainingComputeOptimalLargeLan.html
+++ b/stubs/2022_JordanHoffmann_TrainingComputeOptimalLargeLan.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2022_LongOuyang_TrainingLanguageModelsToFollow.html b/stubs/2022_LongOuyang_TrainingLanguageModelsToFollow.html
index c0cd1b4a..9e0343e8 100644
--- a/stubs/2022_LongOuyang_TrainingLanguageModelsToFollow.html
+++ b/stubs/2022_LongOuyang_TrainingLanguageModelsToFollow.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2022_LucasBeyer_BetterPlainVitBaselinesForImag.html b/stubs/2022_LucasBeyer_BetterPlainVitBaselinesForImag.html
index 72767d53..2310b7b7 100644
--- a/stubs/2022_LucasBeyer_BetterPlainVitBaselinesForImag.html
+++ b/stubs/2022_LucasBeyer_BetterPlainVitBaselinesForImag.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2022_RobinRombach_HighResolutionImageSynthesisWi.html b/stubs/2022_RobinRombach_HighResolutionImageSynthesisWi.html
index 4d472e49..bb34905e 100644
--- a/stubs/2022_RobinRombach_HighResolutionImageSynthesisWi.html
+++ b/stubs/2022_RobinRombach_HighResolutionImageSynthesisWi.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2022_TeroKarras_ElucidatingTheDesignSpaceOfDif.html b/stubs/2022_TeroKarras_ElucidatingTheDesignSpaceOfDif.html
index 4299a862..a0d34767 100644
--- a/stubs/2022_TeroKarras_ElucidatingTheDesignSpaceOfDif.html
+++ b/stubs/2022_TeroKarras_ElucidatingTheDesignSpaceOfDif.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2022_WeixinLiang_MindTheGapUnderstandingTheModa.html b/stubs/2022_WeixinLiang_MindTheGapUnderstandingTheModa.html
index 4c3fc3fc..57a912fa 100644
--- a/stubs/2022_WeixinLiang_MindTheGapUnderstandingTheModa.html
+++ b/stubs/2022_WeixinLiang_MindTheGapUnderstandingTheModa.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2022_ZhuangLiu_AConvnetForThe2020S.html b/stubs/2022_ZhuangLiu_AConvnetForThe2020S.html
index e6d8ac10..8b7ec142 100644
--- a/stubs/2022_ZhuangLiu_AConvnetForThe2020S.html
+++ b/stubs/2022_ZhuangLiu_AConvnetForThe2020S.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2022_ZimingLiu_TowardsUnderstandingGrokkingAn.html b/stubs/2022_ZimingLiu_TowardsUnderstandingGrokkingAn.html
index a8bae068..21c9ebaf 100644
--- a/stubs/2022_ZimingLiu_TowardsUnderstandingGrokkingAn.html
+++ b/stubs/2022_ZimingLiu_TowardsUnderstandingGrokkingAn.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2023_AlexanderKirillov_SegmentAnything.html b/stubs/2023_AlexanderKirillov_SegmentAnything.html
index a8b2c559..34a7f24c 100644
--- a/stubs/2023_AlexanderKirillov_SegmentAnything.html
+++ b/stubs/2023_AlexanderKirillov_SegmentAnything.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2023_AmirhosseinKazemnejad_TheImpactOfPositionalEncodingO.html b/stubs/2023_AmirhosseinKazemnejad_TheImpactOfPositionalEncodingO.html
index a1adf7a9..6cb6a4c6 100644
--- a/stubs/2023_AmirhosseinKazemnejad_TheImpactOfPositionalEncodingO.html
+++ b/stubs/2023_AmirhosseinKazemnejad_TheImpactOfPositionalEncodingO.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2023_CharlieChen_AcceleratingLargeLanguageModel.html b/stubs/2023_CharlieChen_AcceleratingLargeLanguageModel.html
index 68561cf0..9ff0c232 100644
--- a/stubs/2023_CharlieChen_AcceleratingLargeLanguageModel.html
+++ b/stubs/2023_CharlieChen_AcceleratingLargeLanguageModel.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2023_MaximeOquab_Dinov2LearningRobustVisualFeat.html b/stubs/2023_MaximeOquab_Dinov2LearningRobustVisualFeat.html
index 73c7ce06..40d55aa4 100644
--- a/stubs/2023_MaximeOquab_Dinov2LearningRobustVisualFeat.html
+++ b/stubs/2023_MaximeOquab_Dinov2LearningRobustVisualFeat.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2023_MurrayShanahan_RolePlayWithLargeLanguageModel.html b/stubs/2023_MurrayShanahan_RolePlayWithLargeLanguageModel.html
index bbd0df29..5600e7ec 100644
--- a/stubs/2023_MurrayShanahan_RolePlayWithLargeLanguageModel.html
+++ b/stubs/2023_MurrayShanahan_RolePlayWithLargeLanguageModel.html
@@ -315,6 +315,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_OferMShir_OnTheCovarianceHessianRelation.html">“On the covariance-Hessian relation in evolution strategies”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>
diff --git a/stubs/2023_TimoSchick_ToolformerLanguageModelsCanTea.html b/stubs/2023_TimoSchick_ToolformerLanguageModelsCanTea.html
index bdf9c07d..25efcdc8 100644
--- a/stubs/2023_TimoSchick_ToolformerLanguageModelsCanTea.html
+++ b/stubs/2023_TimoSchick_ToolformerLanguageModelsCanTea.html
@@ -314,6 +314,7 @@
 <li class="toctree-l2"><a class="reference internal" href="2019_MingxingTan_EfficientnetRethinkingModelSca.html">“EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks”</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="2019_PreetumNakkiran_DeepDoubleDescentWhereBiggerMo.html">“Deep Double Descent: Where Bigger Models and More Data Hurt”</a></li>
+<li class="toctree-l2"><a class="reference internal" href="2019_RichSutton_TheBitterLesson.html">“The Bitter Lesson”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2019_SamyamRajbhandari_ZeroMemoryOptimizationsTowardT.html">“ZeRO: Memory Optimizations Toward Training Trillion Parameter Models”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AlexeyDosovitskiy_AnImageIsWorth16X16WordsTransf.html">“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”</a></li>
 <li class="toctree-l2"><a class="reference internal" href="2020_AndrewGelman_BayesianWorkflow.html">“Bayesian workflow”</a></li>